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Towards Rule Learning Approaches to Instance-based Ontology Matching
Janssen, Frederik
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Fallahi, Faraz
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Noessner, Jan
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Paulheim, Heiko
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URL:
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http://ceur-ws.org/Vol-868/paper2.pdf
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Additional URL:
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http://www.ke.tu-darmstadt.de/know-a-lod-2012/wp-c...
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Document Type:
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Conference or workshop publication
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Year of publication:
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2012
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Book title:
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KNOW@LOD 2012, Knowledge Discovery and Data Mining Meets Linked Open Data : proceedings of the First International Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data
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The title of a journal, publication series:
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CEUR Workshop Proceedings
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Volume:
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868
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Page range:
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13-18
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Conference title:
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First international workshop on Knowledge Discovery and Data Mining Meets Linked Open Data (Know@LOD)
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Location of the conference venue:
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Heraklion, Greece
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Date of the conference:
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May 27, 2012
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Publisher:
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Völker, Johanna
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Place of publication:
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Aachen, Germany
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Publishing house:
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RWTH Aachen
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ISSN:
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1613-0073
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Publication language:
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English
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Institution:
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School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
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Subject:
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004 Computer science, internet
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Keywords (English):
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Rule Learning , Ontology Matching , Instanced-based
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Abstract:
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Ontology matching approaches have mostly worked on the schema level so far. With the advent of Linked Open Data and the availability of a massive amount of instance information, instance-based approaches become possible. This position paper discusses approaches and challenges for using those instances as input for machine learning algorithms, with a focus on rule learning algorithms, as a means for ontology
matching.
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
 Search Authors in
BASE:
Janssen, Frederik
;
Fallahi, Faraz
;
Noessner, Jan
;
Paulheim, Heiko
Google Scholar:
Janssen, Frederik
;
Fallahi, Faraz
;
Noessner, Jan
;
Paulheim, Heiko
ORCID:
Janssen, Frederik, Fallahi, Faraz, Noessner, Jan and Paulheim, Heiko  ORCID: https://orcid.org/0000-0003-4386-8195
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